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AI Completely Broke the Market--And Most Investors Haven't Noticed Yet

  //stocks-investing.news-articles.net/content/202 .. rket-and-most-investors-haven-t-noticed-yet.html
  Published in Stocks and Investing on Thursday, November 6th 2025 at 8:09 GMT by Seeking Alpha
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1. The Market’s “AI Bubble” Is Already Erupting

The core thesis of the article is that AI has “completely broken the market” by inflating valuations of AI‑centric companies while simultaneously eroding the perceived risk of other tech firms that are only peripheral to the AI boom. The author highlights the AI Index—a portfolio that tracks the largest AI‑related stocks—which outperformed the S&P 500 by more than 70 % in 2023. According to the piece, the AI Index’s return is largely driven by firms such as NVIDIA, Meta Platforms, and Alphabet, all of which have integrated AI into their core products.

A key metric the author uses is the AI‑Adjusted Price‑to‑Earnings (P/E) ratio, calculated by applying a 20 % premium to traditional P/E multiples for firms with significant AI exposure. Under this adjustment, the AI Index now trades at a P/E of 38, compared with the S&P 500’s 22. This premium reflects the market’s anticipation of higher growth rates driven by AI adoption. However, the article points out that the “true” growth impact is still being underestimated because many companies have not yet released their AI‑driven earnings forecasts.

2. The Lag Between AI Innovation and Investor Recognition

A central argument is that investors are still a generation behind in recognizing the full scope of AI’s economic effects. The article cites a survey from Bloomberg (linked in the Seeking Alpha piece) that found only 35 % of retail investors were aware that AI had become a core driver of enterprise software revenue. Moreover, the Bloomberg Tech‑AI Outlook indicates that 80 % of AI‑related patents filed last year were in sectors that traditionally lagged behind hardware, such as logistics and energy.

The author links to a CNBC story that chronicles how AI has started to replace traditional software engineering roles. According to CNBC, a new generation of “prompt‑engineers” can train models with far fewer lines of code, reducing development time from months to weeks. This acceleration is already visible in the earnings of companies like Microsoft and Salesforce, where AI has become the “new CPU” powering product innovation.

3. Valuation Arbitrage Opportunities

The article outlines several concrete arbitrage strategies that savvy investors can employ to capture AI’s upside while mitigating risk:

The article argues that these strategies are especially potent in the current environment, where many AI‑heavy companies are still in a “growth” phase and their valuations have not fully reflected the monetization potential of AI. The author references a Forbes piece that discusses how the market still undervalues the long‑term productivity gains AI can deliver—particularly in supply‑chain optimization and autonomous driving.

4. The Risks of “AI‑Bubbles” and Over‑Hedging

While bullish on AI, the article also warns that the market may have already priced in a significant portion of AI’s impact. The Wall Street Journal link (included in the article) reports that sentiment indicators suggest a “bubble” in AI‑heavy stocks, with the VIX spiking during AI earnings announcements. The author cautions that over‑exposure to AI could lead to sharp corrections if the industry faces regulatory pushback, data‑privacy concerns, or a slowdown in adoption.

Another risk highlighted is the “AI‑short squeeze” phenomenon, where over‑shorted AI stocks could experience dramatic price spikes as short sellers scramble to cover. The Seeking Alpha article uses the recent short‑squeeze of OpenAI‑related shares as a case study, noting that the stock’s volatility was driven largely by speculative shorting rather than fundamental value.

5. Bottom‑Line Takeaway

The article concludes that the AI revolution is not just a technology trend—it is a structural shift in how companies generate value. Investors who ignore the AI premium risk missing out on the next wave of corporate earnings. Conversely, those who over‑invest in AI hype without proper risk management may find themselves exposed to volatility and regulatory uncertainty. The author urges investors to use a balanced approach: incorporate AI exposure into diversified portfolios, monitor the evolving regulatory landscape, and stay informed through reputable sources such as Bloomberg, CNBC, and Forbes.

Supplemental Context from Follow‑Up Links

Bloomberg Tech‑AI Outlook (2024)
The Bloomberg report outlines that AI will contribute an estimated $3.5 trillion to global GDP by 2030, with the tech sector accounting for 40 % of this growth. It also highlights a shift from “software as a service” to “AI as a service,” which could create new revenue streams for cloud providers.

CNBC: AI’s Impact on Software Engineering
CNBC’s interview with a leading AI engineer explains how “prompt‑engineering” allows companies to train models on smaller datasets, cutting costs by up to 30 %. The article emphasizes that companies adopting AI at scale could see revenue growth of 15‑20 % annually over the next five years.

Forbes: AI and Supply‑Chain Optimization
The Forbes article notes that AI is already being used to forecast demand, optimize inventory, and reduce shipping times. Companies such as Amazon and Walmart have reported cost reductions of 10 % per year due to AI‑driven logistics.

Wall Street Journal: AI Bubble Warning
The WSJ editorial warns that while AI valuations have surged, the market still struggles to separate hype from substance. It points to a history of technology bubbles that collapsed when growth prospects failed to materialize, stressing the importance of disciplined valuation metrics.

In summary, the Seeking Alpha article offers a cautionary yet optimistic view of AI’s influence on the market. It underscores the importance of early recognition, diligent research, and risk‑aware investing in a space that promises to redefine corporate value creation for decades to come.